Pandas
pandas.pydata.org › docs › reference › api › pandas.Series.str.encode.html
pandas.Series.str.encode — pandas 3.0.5 documentation
Encode character string in the Series/Index using indicated encoding.
Practical Business Python
pbpython.com › categorical-encoding.html
Guide to Encoding Categorical Values in Python - Practical Business Python
A common alternative approach is called one hot encoding (but also goes by several different names shown below). Despite the different names, the basic strategy is to convert each category value into a new column and assigns a 1 or 0 (True/False) value to the column. This has the benefit of not weighting a value improperly but does have the downside of adding more columns to the data set. Pandas supports this feature using get_dummies.
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Encoding Values In A Pandas Dataframe | Python Tutorial - YouTube
09:03
One Hot Encoder with Python Machine Learning (Scikit-Learn) - YouTube
07:55
How To Encode Categorical Variables Using Pandas - YouTube
21:42
Data Cleaning using Pandas (Part 4): Categorical Encoding - YouTube
Feature Encoding in Python the Pandas way
13:14
Encoding Categorical Values in Pandas for PyTorch (2.2) - YouTube
Pandas
pandas.pydata.org › docs › dev › reference › api › pandas.Series.str.encode.html
pandas.Series.str.encode — pandas 3.0.0.dev0+2728.g7bf6660984 documentation
Encode character string in the Series/Index using indicated encoding.
Pandas
pandas.pydata.org › docs › reference › api › pandas.Series.str.decode.html
pandas.Series.str.decode — pandas 3.0.5 documentation
Encodes strings into bytes in a Series/Index.
Pandas
pandas.pydata.org › pandas-docs › stable › reference › api › pandas.Series.str.encode.html
pandas.Series.str.encode — pandas 3.0.0 documentation
Encode character string in the Series/Index using indicated encoding.
Pandas
pandas.pydata.org › pandas-docs › version › 0.17.0 › generated › pandas.Series.str.encode.html
pandas.Series.str.encode — pandas 0.17.0 documentation
Encode character string in the Series/Index to some other encoding using indicated encoding.
Pandas
pandas.pydata.org › pandas-docs › version › 0.22 › generated › pandas.Series.str.encode.html
pandas.Series.str.encode — pandas 0.22.0 documentation
Encode character string in the Series/Index using indicated encoding.
Turing
turing.com › kb › convert-categorical-data-in-pandas-and-scikit-learn
How to Convert Categorical Data in Pandas and Scikit-learn
We generally use one-hot encoding to solve the disadvantage of label encoding. The strategy is to convert each category into a column and assign it a 1 or 0 value. It is a process of creating dummy variables. ... Import pandas as pd #Creating a dataframe Df = pd.Dataframe({‘City’ : [‘Delhi’,’Mumbai’,’Hydrabad’,’Chennai’,’Bangalore’,’Delhi’,’Hydrabad’,’Banglore’,’Delhi’]})
pandas
pandas.pydata.org › pandas-docs › dev › reference › api › pandas.Series.str.encode.html
pandas.Series.str.encode — pandas 3.1.0.dev0 documentation
Encode character string in the Series/Index using indicated encoding.
Pandas
pandas.pydata.org › pandas-docs › version › 2.2.1 › reference › api › pandas.Series.str.encode.html
pandas.Series.str.encode — pandas 2.2.1 documentation
Encode character string in the Series/Index using indicated encoding.
Pandas
pandas.pydata.org › pandas-docs › version › 0.19 › generated › pandas.Series.str.encode.html
pandas.Series.str.encode — pandas 0.19.2 documentation
Encode character string in the Series/Index using indicated encoding.
TutorialsPoint
tutorialspoint.com › python_pandas › python_pandas_series_str_encode_method.htm
Pandas Series.str.encode() Method
This example demonstrates how to use the Series.str.encode() method to encode a column of strings in a DataFrame using the 'utf-8' encoding. import pandas as pd # Create a DataFrame with a column of strings df = pd.DataFrame({ 'COLUMN1': ['', '', ''] }) # Encode strings using 'utf-8' encoding result = df['COLUMN1'].str.encode('utf-8') print("Input DataFrame:") print(df) print("\nDataFrame column after calling str.encode('utf-8'):") print(result)
Pandas
pandas.pydata.org › pandas-docs › stable › generated › pandas.Series.str.encode.html
pandas.Series.str.encode — pandas 2.2.2 documentation
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Top answer 1 of 2
3
You can use this solution implemented to pandas by Series.apply:
from Crypto.Cipher import XOR
import base64
def encrypt(key, plaintext):
cipher = XOR.new(key)
return base64.b64encode(cipher.encrypt(plaintext))
def decrypt(key, ciphertext):
cipher = XOR.new(key)
return cipher.decrypt(base64.b64decode(ciphertext))
load['Encoded_Column'] = load['F'].apply(lambda x: encrypt('password',x))
load['Decoded_Column'] = (load['Encoded_Column'].apply(lambda x: decrypt('password', x))
.str.decode("utf-8"))
print (load)
A B C D E F Encoded_Column Decoded_Column
0 a 4 7 1 5 a b'EQ==' a
1 b 5 8 3 3 a b'EQ==' a
2 c 4 9 5 6 a b'EQ==' a
3 d 5 4 4 9 b b'Eg==' b
4 e 5 2 2 2 b b'Eg==' b
5 f 4 0 0 4 b b'Eg==' b
Another solution:
import base64
def encode(key, clear):
enc = []
for i in range(len(clear)):
key_c = key[i % len(key)]
enc_c = chr((ord(clear[i]) + ord(key_c)) % 256)
enc.append(enc_c)
return base64.urlsafe_b64encode("".join(enc).encode()).decode()
def decode(key, enc):
dec = []
enc = base64.urlsafe_b64decode(enc).decode()
for i in range(len(enc)):
key_c = key[i % len(key)]
dec_c = chr((256 + ord(enc[i]) - ord(key_c)) % 256)
dec.append(dec_c)
return "".join(dec)
load['Encoded_Column'] = load['F'].apply(lambda x: encode('password',x))
load['Decoded_Column'] = load['Encoded_Column'].apply(lambda x: decode('password', x))
Or use list comprehension:
load['Encoded_Column'] = [encode('password',x) for x in load['F']]
load['Decoded_Column'] = [decode('password', x) for x in load['Encoded_Column']]
print (load)
A B C D E F Encoded_Column Decoded_Column
0 a 4 7 1 5 a w5E= a
1 b 5 8 3 3 a w5E= a
2 c 4 9 5 6 a w5E= a
3 d 5 4 4 9 b w5I= b
4 e 5 2 2 2 b w5I= b
5 f 4 0 0 4 b w5I= b
2 of 2
0
import pandas as pd
import binascii
load = pd.DataFrame({'A':list('abcdef'),
'B':[4,5,4,5,5,4],
'C':[7,8,9,4,2,0],
'D':[1,3,5,4,2,0],
'E':[5,3,6,9,2,4],
'F':[binascii.hexlify(x.encode()) for x in 'aaabbb']
})
A B C D E F
0 a 4 7 1 5 b'61'
1 b 5 8 3 3 b'61'
2 c 4 9 5 6 b'61'
3 d 5 4 4 9 b'62'
4 e 5 2 2 2 b'62'
5 f 4 0 0 4 b'62'
# decode
binascii.unhexlify(load.loc[1]['F']).decode('utf-8') -->> 'a'
example
print(binascii.hexlify('HelloWorld'.encode())) --> b'48656c6c6f576f726c64'
print(binascii.unhexlify('48656c6c6f576f726c64'.encode())) --> b'HelloWorld'
Pandas
pandas.pydata.org › pandas-docs › version › 1.0.0 › reference › api › pandas.Series.str.encode.html
pandas.Series.str.encode — pandas 1.0.0 documentation
Encode character string in the Series/Index using indicated encoding.
Pandas
pandas.pydata.org › pandas-docs › version › 1.0.1 › reference › api › pandas.Series.str.encode.html
pandas.Series.str.encode — pandas 1.0.1 documentation
Encode character string in the Series/Index using indicated encoding.